Gaming scheme using general mood information

ABSTRACT

Technologies are generally described for an general mood adding scheme in a cloud-based game system. In some examples, a method performed under control of a computing device may include receiving from a raw database at least one set of facial expression data, each of the at least one set of facial expression data being accompanied by time information and location information, clustering a geographic area to form at least one cluster based at least in part on the at least one set of facial expression data, and storing the at least one cluster in a map database corresponding to the area.

BACKGROUND

GPS technologies have experienced phenomenal growth in the last fewyears. Game providers have adapted these technologies for position-basedgames. For example, games involving physical searches, such asorienteering game, treasure hunts, tag etc., may utilize a GPS system todetermine the location of one or more players.

SUMMARY

In an example, a method performed under control of a computing devicemay include receiving, from a raw database, at least one set of facialexpression data, each of the at least one set of facial expression databeing accompanied by time information and location information;clustering a geographic area to form at least one cluster based at leastin part on the at least one set of facial expression data; and storingthe at least one cluster in a map database corresponding to thegeographic area.

In an example, a method performed under control of a computing devicemay include receiving at least one image captured by at least one cameralocated in a geographic area, obtaining at least one set of facialexpression data from the at least one captured image, each of the atleast one set of facial expression data being accompanied by timeinformation and location information; clustering the geographic area toform at least one cluster based at least in part on the at least one setof facial expression data; and storing the at least one cluster in a mapdatabase corresponding to the geographic area.

In an example, a computing device may include a receiving unitconfigured to receive from a raw database at least one set of facialexpression data, each of the at least one set of facial expression databeing accompanied by time information and location information; aclustering unit configured to perform a spatiotemporal clustering of ageographic area to form at least one cluster based at least in part onthe at least one set of facial expression data; and a storing unitconfigured to store the at least one cluster in a map databasecorresponding to the geographic area.

In an example, a computer-readable storage medium having stored thereoncomputer-executable instructions that, in response to execution, cause acomputing device to perform operations that may include receiving from araw database at least one set of facial expression data, each of the atleast one set of facial expression data being accompanied by timeinformation and location information; clustering a geographic area toform at least one cluster based at least in part on the at least one setof facial expression data; and storing the at least one cluster in a mapdatabase corresponding to the geographic area.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

The foregoing and other features of this disclosure will become moreapparent from the following description and appended claims, taken inconjunction with the accompanying drawings. Understanding that thesedrawings depict only several embodiments in accordance with thedisclosure and are, therefore, not to be considered limiting of itsscope, the disclosure will be described with additional specificity anddetail through use of the accompanying drawings, in which:

FIG. 1 schematically shows an illustrative example of an environment inwhich general mood information is obtained at multiple points, arrangedin accordance with at least some embodiments described herein;

FIG. 2 schematically shows an illustrative example of a gaming schemesystem configuration installed at multiple points, arranged inaccordance with at least some embodiments described herein;

FIG. 3 schematically shows an illustrative example of a systemenvironment for clustering a geographic area with general moodinformation, arranged in accordance with at least some embodimentsdescribed herein;

FIGS. 4A and 4B schematically show an illustrative example of clusteringresults based on facial expressions of people in a geographic region,arranged in accordance with at least some embodiments described herein;

FIG. 5 shows a schematic block diagram illustrating an examplearchitecture of a computing device for a gaming scheme using generalmood information, arranged in accordance with at least some embodimentsdescribed herein;

FIG. 6 shows an example flow diagram of a process of a computing devicefor a gaming scheme using general mood information, arranged inaccordance with at least some embodiments described herein;

FIG. 7 illustrates computer program products that may be utilized toprovide a gaming scheme using general mood information, arranged inaccordance with at least some embodiments described herein; and

FIG. 8 is a block diagram illustrating an example computing device thatmay be utilized to provide a gaming scheme using general moodinformation, arranged in accordance with at least some embodimentsdescribed herein.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented herein. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe drawings, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

This disclosure is generally drawn, inter alia, to methods, apparatuses,systems, devices, and computer program products related to gaming schemeusing general mood information.

Technologies are generally described for a game system in which acomputing device may acquire images of people in a particular geographicregion using multiple cameras installed in the geographic region.Non-limiting examples of such a particular geographic region may includea city, county, town, hamlet, neighborhood, etc. The computing devicemay recognize facial expressions of people in the particular geographicregion using facial recognition technologies, and record the facialexpressions and time and place information relating to the facialexpressions in a raw database. Further, the computing device mayspatiotemporally cluster a geographic area of the geographic regionusing the facial expressions and the time and place information and formone or more clusters with respective general mood information. Thegeneral mood information may reveal or indicate an emotion relating toor determined based on the facial expressions of the people at aparticular time in a particular place. By way of example, but notlimitation, the general mood information may include delight, anger,sorrow, joy, shock, fear, abomination and indifference. The general moodinformation may be attached to a digital map of the geographic regionstored in a map database, and game providers may utilize the digital mapof the geographic region for their games, such as actual position-basedgames.

By way of example, but not limitation, images of people passing by astreet A in the geographic region at 1 p.m. may be acquired with camerasinstalled around the street A, and facial expressions may be recognizedusing facial recognition technologies. If majority of recognized facialexpressions may be categorized as “delight,” the street A at 1 p.m. maybe clustered as “delight,” and general mood information of “delight” at1 p.m. may be attached to the street A in the digital map.

Further, external factors, such as population density, weatherconditions, and information about events being held in the vicinity of aparticular place at a particular time (e.g., local current events),together with the recognized facial expressions of the people, may beacquired and stored in the raw database, and general mood informationincluding such external factors may be attached to the digital map. Byobtaining a correlation between the external factors and the one or moreclusters, it is possible to attach information as to how the generalmood information changes according to the external factors.

By way of example, but not limitation, the map database may be a clouddatacenter, and cloud computing technologies may be employed fordatabase management, data update and information distribution.Therefore, it may be possible to obtain and periodically update thedigital map by various game providers and the game providers may be ableto use the digital map for their games.

In some embodiments, a game player, who is playing an actualposition-based game utilizing the digital map with the general moodinformation stored in the map database, may refer to the general moodinformation at a particular time in a particular place with indexes oftime, place (and event information, if any) from the map database, anduse the general mood information while playing of the game. By way ofexample, but not limitation, for a treasure-hunting game, the gameplayer may want to ask passersby for a hint in order to find a treasure.In such a case, the game player may refer to the general moodinformation at the present time in the place where the game player islocated. If the general mood information indicates “delight,” the gameplayer may assume that it may be easy to get the hint from thepassersby; but if the general mood information indicates “anger,” thegame player may assume that it may not be easy to get the hint from thepassersby. In this way, general mood information may be used for gamesin various ways.

FIG. 1 schematically shows an illustrative example of an environment inwhich general mood information is obtained at multiple points, arrangedin accordance with at least some embodiments described herein.

As depicted in FIG. 1, general mood information may be obtained atmultiple points 110 to 150, and one or more cameras for capturing imagesof people may be installed at each of respective multiple points 110 to150. Each camera may capture images of people who pass by the camera. Byway of example, but not limitation, images of people crossing at acrosswalk may be captured with a camera installed at point 120.

In some embodiments, each of the cameras may be connected to a computingdevice, which may perform facial recognition processing of the capturedimages and further obtain facial expressions from the captured images.The computing device may include a personal computer, which may beinstalled close to each camera. In such cases, the facial expressionsobtained by any of the computing device may be used to determine generalmood information around respective points 110 to 150. In someembodiments, a sensor for measuring external factors (for example, butnot as a limitation, a temperature, humidity, population density, etc.)may be installed at each of points 110 to 150 to measure the externalfactors, based on which, along with the facial expressions, the generalmood information may be determined.

FIG. 2 schematically shows an illustrative example of a gaming schemesystem configuration installed at multiple points, arranged inaccordance with at least some embodiments described herein.

As depicted in FIG. 2, a gaming scheme system, which may be installed ateach of multiple points 110 to 150, may include at least one camera 210,a facial expression recognition unit 220, a sensor 230 for measuringexternal factors, and an external factor input/output unit 240.

Camera 220, which may be installed at a particular one of points110-150, may be configured to acquire images including facialexpressions of people passing by, and transmit the acquired images tofacial expression recognition unit 220.

Facial expression recognition unit 220 may be configured to recognizethree-dimensional positions and facial expressions of the people fromthe images received from camera 210 and record the facial expressionstogether with an image acquisition time and an acquisition location in araw database, which will be described more in detail below. As depictedin FIG. 2, people whose images are captured by camera 210 may makevarious facial expressions, such as smiles, frowns, or even a lack ofexpression. A technology for recognizing such various facial expressionsmay be employed from various conventional facial recognitiontechnologies, and persons skilled in the art would appreciate that it isnot limited to a particular facial recognition technology. By way ofexample, but not limitation, such facial expressions may be recognizedbased on the positions and forms of eyebrows, eyes and mouth by using acommercial software, such as faceAPI(http://www.seeingmachines.com/product/faceapi/). The recognized facialexpressions may be categorized into various general moods by using, forexample, SVM (Support Vector Machine). Further, OKAO® Vision of OmronCo. (http://www.omron.co.jp/press/2007/09/c0905 a.html) may be employedto determine a degree of smile of each people.

Sensor 230, which may be installed at a particular one of points110-150, may be configured to measure external factors of a particulargeographic region. In some embodiments, the external factors may includepopulation density, weather conditions, and information about eventsbeing held in the vicinity of a particular place at a particular time.By way of example, but not limitation, with regard to population densityas one of the external factors, sensor 230 may be a headcount deviceusing infrared light. With regard to weather conditions as one of theexternal factors, sensor 230 may be a weather sensor for measuringilluminance, temperature, humidity, and atmospheric pressure. Further,with regard to local event information as one of the external factors,sensor 230 may be a keyboard or a mouse that enables people to inputevent information.

External factor input/output unit 240 may be configured to receiveexternal factors from sensor 220 and record, in the raw database, theexternal factors together with time information and location informationcorresponding thereto.

FIG. 3 schematically shows an illustrative example of a systemenvironment for clustering a geographic area with general moodinformation, arranged in accordance with at least some embodimentsdescribed herein.

As depicted in FIG. 3, a multiple number of gaming scheme systems, mayeach include separate embodiments of camera 210, facial expressionrecognition unit 220, sensor 230 and external factor input/output unit240, may be connected, via a network 310, to a raw database 320. Asdescribed above, facial expression recognition unit 220 may recognizethree-dimensional positions and facial expressions of the people fromthe images received from camera 210, and record the facial expressionstogether with an image acquisition time and an acquisition location inraw database 320 via network 310. In some embodiments, images of facialexpressions may be stored in raw database 320 whenever an image isacquired from camera 210. In some other embodiments, images of facialexpressions may be stored in raw database 320 periodically.

FIG. 3 illustrates camera 210 and facial expression recognition unit 220provided as one set; and, after recognizing facial expressions, eachfacial expression recognition unit 220 may provide data sets of therecognized facial expressions together with an acquisition time and anacquisition location and to raw database 320, via network 310, forstorage there. However, the present disclosure is not limited thereto.In some embodiments, multiple cameras may be connected to one facialexpression recognition unit 220 via network 310; and the facialexpression recognition unit 220 may receive images from each of themultiple cameras, perform facial recognition processing, and store theresults in raw database 320. Similarly, multiple sensors may beconnected to one external factor input/output unit via network 310, andthe external factor input/output unit 240 may receive external factorsfrom each of the multiple sensors 230, and store the received externalfactors together with its corresponding time and place information inraw database 320.

A computing device 330 may be configured to spatiotemporally cluster thegeographic region using the data sets of time, place and facialexpressions stored in raw database 320 to form one or more clusters. Insome embodiments, computing device 330 may perform the clustering basedon data sets which may be accumulated for a predetermined period.Details of the clustering will be described below with reference toFIGS. 4A and 4B. In some embodiments, the clusters formed by computingdevice 330 may include general mood information that reveals an emotionrelating to the facial expressions.

A map database 340 may store a digital map of an actual town, and theclusters may be attached to the digital map. In some embodiments, eachof the clusters including corresponding general mood information at aparticular time may be attached to a corresponding area in the digitalmap. Details of the attaching will be described below with reference toFIGS. 4A and 4B.

In some embodiments, map database 340 may be a cloud datacenter.Further, cloud computing technologies may be employed for databasemanagement, data update and information distribution of map database340. In such cases, it may be possible to obtain and periodically updatethe digital map having the clusters attached thereto by various gameproviders and the game providers may be able to use the digital map fortheir games.

In some embodiments, a game player, who is playing an actualposition-based game utilizing the digital map, may refer to the generalmood information at a particular time in a particular place with indexesof time and place from map database 340 and use the general moodinformation for the game playing. By way of example, but not limitation,in case of a treasure-hunting game, if a game player finds a treasure ingeographic region in which the generation mood is designated as“delight”, double points may be given to the game player. Alternatively,in a game of tag, a game player may not be able to hide in geographicregion in which the general mood is designated as “anger”.

FIGS. 4A and 4B schematically show an illustrative example of clusteringresults based on facial expressions of people in a geographic region,arranged in accordance with at least some embodiments described herein.

As depicted in FIG. 4A, by using facial expressions stored in rawdatabase 320, geographic region {circle around (A)}, geographic region{circle around (B)}, geographic region {circle around (C)}, andgeographic region {circle around (D)} may be clustered by the respectivegeneral moods “delight,” “anger,” “sorrow,” and a “joy.” By way ofexample, facial expressions of people passing through geographic region{circle around (A)} at 1 p.m. may be acquired by a camera installed atgeographic region {circle around (A)} and recognized, and if themajority of images of passersby have facial expressions that may becategorized as those of “delight,” geographic region {circle around (A)}at 1 p.m. may be clustered as having the general mood “delight.”

Clusters may be changed over time. As depicted in FIG. 4B, at 6 p.m.,geographic region {circle around (A)}, which was clustered as having thegeneral mood of “delight” at 1 p.m. may be combined with geographicregion {circle around (B)}0 to become geographic region {circle around(E)}, which may be clustered the general mood of “neutral” or“indifference,” and geographic region {circle around (D)} may be dividedinto two clusters, i.e. geographic region {circle around (D)} having thegeneral mood “joy” and geographic region {circle around (A)} having thegeneral mood “delight.”

As described above, the presently described clustering may be performedto allocate trending moods, as expressed in captured images of facialexpression data corresponding to passerbys at a particular time at aparticular place. By way of example, but not limitation, conventionaltechnologies, such as an ISODATA (Iterative Self-Organizing DataAnaylysis Technique Algorithm) or K-means clustering, which is a methodof cluster analysis that aims to partition n observations into kclusters in which each observation belongs to the cluster with thenearest mean, may be employed for the clustering.

FIG. 5 shows a schematic block diagram illustrating an examplearchitecture of a computing device for gaming scheme using general moodinformation, arranged in accordance with at least some embodimentsdescribed herein.

As depicted, computing device 330 may include a receiving unit 510, aclustering unit 520 and a storing unit 530. Although illustrated asdiscrete components, various components may be divided into additionalcomponents, combined into fewer components, or eliminated altogetherwhile being contemplated within the scope of the disclosed subjectmatter.

Receiving unit 510 may be configured to receive from raw database 320 atleast one set of facial expression data. In some embodiments, each setof facial expression data may be accompanied by time information andlocation information. In some embodiments, each set of facial expressiondata may include information regarding people's facial expressions(e.g., delight, anger, sorrow, joy, shock, fear, abomination,indifference, etc.) gleaned from images acquired by camera 210 andfacial expression recognition unit 220, which may be installed in aparticular point in a geographical region, and stored together with anacquisition time and an acquisition location in raw database 320.

Clustering unit 520 may be configured to perform a spatiotemporalclustering of a geographic region to form at least one cluster based atleast in part on general mood information corresponding to stored facialexpression data. That is, clustering unit 520 may spatiotemporallycluster the set of facial expression data having time, place and facialexpressions received from raw database 320, and the clustering may beperformed to allocate trending facial expression data corresponding to aparticular time and a particular place. Each cluster may contain generalmood information. The general mood information may include delight,anger, sorrow, joy, shock, fear, abomination and neutral or indifferentstates.

Storing unit 530 may be configured to store the at least one cluster inmap database 340 corresponding to the particular geographic region. Thatis, storing unit 530 may store the clustering result of clustering unit520 in map database 340 and attach the general mood information based onthe facial expressions in the particular place at the particular time toa simple geographic map. Thus, game providers can use such a map fortheir games.

In some embodiments, receiving unit 510 may be further configured toreceive from raw database 320 at least one external factor, and storingunit 530 may be further configured to store the at least one externalfactor in map database 340. In some embodiments, each external factormay relate to one of the at least one set of facial expression data. Byway of example, but not limitation, the at least one external factor mayinclude population density, weather information and event information.

FIG. 6 shows an example flow diagram of a process of a computing devicefor providing a gaming scheme using general mood information, arrangedin accordance with at least some embodiments described herein. Themethod in FIG. 6 may be implemented in or by computing device 330, whichmay include receiving unit 510, clustering unit 520 and storing unit 530discussed above. An example process may include one or more operations,actions, or functions as illustrated by one or more blocks S600, S610and/or S620. Although illustrated as discrete blocks, various blocks maybe divided into additional blocks, combined into fewer blocks, oreliminated, depending on the desired implementation. Processing maybegin at block 600.

At block S600 (Receiving from Raw Database Set of Facial ExpressionData), computing device 330 may receive, from raw database 320, at leastone set of facial expression data which is accompanied by timeinformation and location information. The time information relates to atime when an image for acquiring facial expression data was captured bycamera 210, and the location information relates to a location where theimage was captured. In at least some embodiments, the image was capturedby camera 210 Processing may continue from block S600 to block S610.

At block S610 (Clustering Geographic Area), computing device 330 maycluster a geographic area to form at least one cluster based at least inpart on the at least one set of facial expression data. In someembodiments, computing device 330 may spatiotemporally cluster the atleast one set of facial expression data having time, place, and facialexpression received from raw database 320, and the clustering may beperformed to allocate trending facial expression data corresponding to aparticular time and a particular geographical region. Each cluster maycontain general mood information. The general mood information mayinclude delight, anger, sorrow, joy, shock, fear, abomination andneutral or indifferent states. Processing may continue from block S610to block S620.

At block S620 (Storing Cluster in Map Database), computing device 330may store at least one cluster in map database 340 corresponding to thearea. That is, cluster information may be stored in map database 340corresponding to the area and town general mood information based onfacial expressions in a particular area at a particular time may beattached to a simple geographic map. Thus, game providers can use such amap for their games.

One skilled in the art will appreciate that, for this and otherprocesses and methods disclosed herein, the functions performed in theprocesses and methods may be implemented in differing order.Furthermore, the outlined steps and operations are only provided asexamples, and some of the steps and operations may be optional, combinedinto fewer steps and operations, or expanded into additional steps andoperations without detracting from the essence of the disclosedembodiments.

FIG. 7 illustrates computer program products that may be utilized toprovide a gaming scheme using general mood information, in accordancewith at least some embodiments described herein. A program product 700may include a signal bearing medium 702. Signal bearing medium 702 mayinclude one or more instructions 704 that, when executed by, forexample, a processor, may provide the functionality described above withrespect to FIGS. 1-6. By way of example, instructions 704 may include:one or more instructions for receiving from a raw database at least oneset of facial expression data, each of the at least one set of facialexpression data being accompanied by time information and locationinformation; clustering a geographic area to form at least one clusterbased at least in part on the at least one set of facial expressiondata; and storing the at least one cluster in a map databasecorresponding to the area. Thus, for example, referring to FIG. 5,computing device 330 may undertake one or more of the blocks shown inFIG. 6 in response to instructions 704.

In some implementations, signal bearing medium 702 may encompass acomputer-readable medium 706, including, but not limited to, a hard diskdrive, a CD, a DVD, a digital tape, memory, etc. In someimplementations, signal bearing medium 702 may encompass a recordablemedium 708, including, but not limited to, memory, read/write (R/W) CDs,R/W DVDs, etc. In some implementations, signal bearing medium 702 mayencompass a communications medium 710, including, but not limited to, adigital and/or an analog communication medium (e.g., a fiber opticcable, a waveguide, a wired communications link, a wirelesscommunication link, etc.). Thus, for example, program product 700 may beconveyed to one or more modules of server 105 by an RF signal bearingmedium 702, where the signal bearing medium 702 is conveyed by awireless communications medium 710 (e.g., a wireless communicationsmedium conforming with the IEEE 702.11 standard).

FIG. 8 is a block diagram illustrating an example computing device thatmay be utilized to provide a gaming scheme using general moodinformation, in accordance with at least some embodiments describedherein. In a very basic configuration 802, computing device 800typically includes one or more processors 804 and a system memory 806. Amemory bus 808 may be used for communicating between processor 804 andsystem memory 806.

Depending on the desired configuration, processor 804 may be of any typeincluding but not limited to a microprocessor (μP), a microcontroller(μC), a digital signal processor (DSP), or any combination thereof.Processor 804 may include one more levels of caching, such as a levelone cache 810 and a level two cache 812, a processor core 814, andregisters 816. An example processor core 814 may include an arithmeticlogic unit (ALU), a floating point unit (FPU), a digital signalprocessing core (DSP Core), or any combination thereof. An examplememory controller 818 may also be used with processor 804, or in someimplementations memory controller 818 may be an internal part ofprocessor 804.

Depending on the desired configuration, system memory 806 may be of anytype including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. System memory 806 may include an operating system 820, one ormore applications 822, and program data 824. Application 822 may includeinstructions 826 that may be arranged to perform the functions asdescribed herein including the actions described with respect to thecomputing device 330 architecture as shown in FIG. 5 or including theactions described with respect to the flow charts shown in FIG. 6. Insome examples, application 822 may be arranged to operate with programdata 824 on an operating system 820 such that implementations forinstructions for an electronic device as described herein.

Computing device 800 may have additional features or functionality, andadditional interfaces to facilitate communications between basicconfiguration 802 and any required devices and interfaces. For example,a bus/interface controller 830 may be used to facilitate communicationsbetween basic configuration 802 and one or more data storage devices 832via a storage interface bus 834. Data storage devices 832 may beremovable storage devices 836, non-removable storage devices 838, or acombination thereof. Examples of removable storage and non-removablestorage devices include magnetic disk devices such as flexible diskdrives and hard-disk drives (HDD), optical disk drives such as compactdisk (CD) drives or digital versatile disk (DVD) drives, solid statedrives (SSD), and tape drives to name a few. Example computer storagemedia may include volatile and nonvolatile, removable and non-removablemedia implemented in any method or technology for storage ofinformation, such as computer readable instructions, data structures,program modules, or other data.

System memory 806, removable storage devices 836 and non-removablestorage devices 838 are examples of computer storage media. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical storage, magnetic cassettes, magnetic tape, magneticdisk storage or other magnetic storage devices, or any other mediumwhich may be used to store the desired information and which may beaccessed by computing device 800. Any such computer storage media may bepart of computing device 800.

Computing device 800 may also include an interface bus 840 forfacilitating communication from various interface devices (e.g., outputdevices 842, peripheral interfaces 844, and communication devices 846)to basic configuration 802 via bus/interface controller 830. Exampleoutput devices 842 include a graphics processing unit 848 and an audioprocessing unit 850, which may be configured to communicate to variousexternal devices such as a display or speakers via one or more AN ports852. Example peripheral interfaces 844 include a serial interfacecontroller 854 or a parallel interface controller 856, which may beconfigured to communicate with external devices such as input devices(e.g., keyboard, mouse, pen, voice input device, touch input device,etc.) or other peripheral devices (e.g., printer, scanner, etc.) via oneor more I/O ports 858. An example communication device 846 includes anetwork controller 860, which may be arranged to facilitatecommunications with one or more other computing devices 862 over anetwork communication link via one or more communication ports 864.

The network communication link may be one example of a communicationmedia. Communication media may typically be embodied by computerreadable instructions, data structures, program modules, or other datain a modulated data signal, such as a carrier wave or other transportmechanism, and may include any information delivery media. A “modulateddata signal” may be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.By way of example, and not limitation, communication media may includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), microwave,infrared (IR) and other wireless media. The term computer readable mediaas used herein may include both storage media and communication media.

Computing device 800 may be implemented as a portion of a small-formfactor portable (or mobile) electronic device such as a cell phone, apersonal data assistant (PDA), a personal media player device, awireless web-watch device, a personal headset device, an applicationspecific device, or a hybrid device that include any of the abovefunctions. Computing device 800 may also be implemented as a personalcomputer including both laptop computer and non-laptop computerconfigurations.

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its spirit and scope, as will be apparentto those skilled in the art. Functionally equivalent methods andapparatuses within the scope of the disclosure, in addition to thoseenumerated herein, will be apparent to those skilled in the art from theforegoing descriptions. Such modifications and variations are intendedto fall within the scope of the appended claims. The present disclosureis to be limited only by the terms of the appended claims, along withthe full scope of equivalents to which such claims are entitled. It isto be understood that this disclosure is not limited to particularmethods, reagents, compounds, compositions or biological systems, whichcan, of course, vary. It is also to be understood that the terminologyused herein is for the purpose of describing particular embodimentsonly, and is not intended to be limiting.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for sakeof clarity.

It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to embodiments containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should be interpreted to mean “at least one”or “one or more”); the same holds true for the use of definite articlesused to introduce claim recitations. In addition, even if a specificnumber of an introduced claim recitation is explicitly recited, thoseskilled in the art will recognize that such recitation should beinterpreted to mean at least the recited number (e.g., the barerecitation of “two recitations,” without other modifiers, means at leasttwo recitations, or two or more recitations). Furthermore, in thoseinstances where a convention analogous to “at least one of A, B, and C,etc.” is used, in general such a construction is intended in the senseone having skill in the art would understand the convention (e.g., “asystem having at least one of A, B, and C” would include but not belimited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, etc.). In those instances where a convention analogous to “atleast one of A, B, or C, etc.” is used, in general such a constructionis intended in the sense one having skill in the art would understandthe convention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). It will be further understood by those withinthe art that virtually any disjunctive word and/or phrase presenting twoor more alternative terms, whether in the description, claims, ordrawings, should be understood to contemplate the possibilities ofincluding one of the terms, either of the terms, or both terms. Forexample, the phrase “A or B” will be understood to include thepossibilities of “A” or “B” or “A and B.”

In addition, where features or aspects of the disclosure are describedin terms of Markush groups, those skilled in the art will recognize thatthe disclosure is also thereby described in terms of any individualmember or subgroup of members of the Markush group.

As will be understood by one skilled in the art, for any and allpurposes, such as in terms of providing a written description, allranges disclosed herein also encompass any and all possible subrangesand combinations of subranges thereof. Any listed range can be easilyrecognized as sufficiently describing and enabling the same range beingbroken down into at least equal halves, thirds, quarters, fifths,tenths, etc. As a non-limiting example, each range discussed herein canbe readily broken down into a lower third, middle third and upper third,etc. As will also be understood by one skilled in the art all languagesuch as “up to,” “at least,” and the like include the number recited andrefer to ranges which can be subsequently broken down into subranges asdiscussed above. Finally, as will be understood by one skilled in theart, a range includes each individual member. Thus, for example, a grouphaving 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, agroup having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells,and so forth.

From the foregoing, it will be appreciated that various embodiments ofthe present disclosure have been described herein for purposes ofillustration, and that various modifications may be made withoutdeparting from the scope and spirit of the present disclosure.Accordingly, the various embodiments disclosed herein are not intendedto be limiting, with the true scope and spirit being indicated by thefollowing claims.

1. A method performed under control of a computing device, comprising:receiving from a raw database at least one set of facial expressiondata, each of the at least one set of facial expression data beingaccompanied by time information and location information; clustering ageographic area to form at least one cluster based at least in part onthe at least one set of facial expression data; and storing the at leastone cluster in a map database corresponding to the geographic area. 2.The method of claim 1, wherein each of the at least one set of facialexpression data is obtained from at least one image, and the at leastone image is captured by a camera at a time corresponding to the timeinformation and at a location corresponding to the location information.3. The method of claim 1, wherein each of the at least one set of facialexpression data is obtained from at least one image, and the at leastone image is captured by a camera for a predetermined periodcorresponding to the time information and at a location corresponding tothe location information.
 4. The method of claim 1, wherein the at leastone cluster includes general mood information, and the general moodinformation is one that reveals an emotion.
 5. The method of claim 1,wherein the clustering includes a spatiotemporal clustering, and each ofthe at least one cluster includes temporal information and spatialinformation within the geographic area.
 6. The method of claim 5,wherein the storing includes attaching each of the at least one clusterto the map database based at least in part on the temporal informationand the spatial information.
 7. The method of claim 1, furthercomprising: receiving from the raw database at least one externalfactor; and storing the at least one external factor in the mapdatabase.
 8. The method of claim 7, wherein each of the at least oneexternal factor includes at least one of population density, weatherconditions and event information.
 9. The method of claim 1, wherein atleast one of the raw database and the map database is stored in a clouddata center.
 10. A method performed under control of a computing device,comprising: receiving at least one image captured by at least one cameralocated in a geographic area; obtaining at least one set of facialexpression data from the at least one captured image, each of the atleast one set of facial expression data being accompanied by timeinformation and location information; clustering the geographic area toform at least one cluster based at least in part on the at least one setof facial expression data; and storing the at least one cluster in a mapdatabase corresponding to the geographic area.
 11. The method of claim10, wherein the at least one cluster includes general mood information,and the general mood information is one that reveals an emotion.
 12. Themethod of claim 10, wherein the clustering includes a spatiotemporalclustering, and each of the at least one cluster includes temporalinformation and spatial information within the geographic area.
 13. Themethod of claim 12, wherein the storing includes attaching each of theat least one cluster to the map database based at least in part on thetemporal information and the spatial information.
 14. A computingdevice, comprising: a receiving unit configured to receive from a rawdatabase at least one set of facial expression data, each of the atleast one set of facial expression data being accompanied by timeinformation and location information; a clustering unit configured toperform a spatiotemporal clustering of a geographic area to form atleast one cluster based at least in part on the at least one set offacial expression data; and a storing unit configured to store the atleast one cluster in a map database corresponding to the geographicarea.
 15. The computing device of claim 14, wherein each of the at leastone set of facial expression data is obtained from at least one image,and the at least one image is captured by a camera at a timecorresponding to the time information and at a location corresponding tothe location information.
 16. The computing device of claim 14, whereinthe at least one cluster includes general mood information, and thegeneral mood information is one that reveals an emotion.
 17. Thecomputing device of claim 14, wherein each of the at least one clusterincludes temporal information and spatial information within thegeographic area, and wherein the storing unit further configured toattach each of the at least one cluster to the map database based atleast in part on the temporal information and the spatial information.18. The computing device of claim 14, wherein the receiving unit furtherconfigured to receive from the raw database at least one externalfactor, each of the at least one external factor relating to one of theat least one set of facial expression data, and wherein the storing unitfurther configured to store the at least one external factor in the mapdatabase.
 19. The computing device of claim 18, wherein each of the atleast one external factor includes at least one of population density,weather conditions and event information.
 20. The computing device ofclaim 14, wherein at least one of the raw database and the map databaseis stored in a cloud data center. 21.-23. (canceled)